| 基于模糊C均值的异常流量检测模型 |
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| 引用本文： | 李雪琴.基于模糊C均值的异常流量检测模型[J].赣南师范学院学报,2009,30(6):89-91. |
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| 作者姓名： | 李雪琴 |
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| 作者单位： | 赣南师范学院高职学院,江西赣州,341000 |
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| 摘 要： | 对网络进行流量异常检测，流量出现异常后再对数据包进行分析，通过这种方法能够降低系统开销，聚类算法是一种有效的异常入侵检测方法，可用在网络流量异常检测中，用于判定当前网络流量是否出现异常，本文将模糊C均值算法应用于流量异常检测模型中，通过实验，该模型能够有效检测出流量的异常状态．
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| 关 键 词： | 流量异常检测 聚类算法 模糊C均值 |
Anomaly Network Traffc Detection Model Based on Fuzzy C-Means Clustering Algorithm |
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| LI Xue-qiin.Anomaly Network Traffc Detection Model Based on Fuzzy C-Means Clustering Algorithm[J].Journal of Gannan Teachers' College(Social Science(2)),2009,30(6):89-91. |
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| Authors: | LI Xue-qiin |
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| Institution: | LI Xue-qiin Gannan Normal University, Ganzhou 341000, China) |
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| Abstract: | It should be more efficient to detect the anomaly of network traffic firstly rather than to analyze the data packets directly.This method could reduce the cost of system resources.Clustering is an effective method of anomaly intrusion detection.It's always used in anomaly network traffic detection.It could detect the current anomaly network traffic.Fuzzy C-Means clustering algorithm which is designed for network traffic detection model has been put forward in this paper.The experiment shows that the model is effective which applied in the detection of anomaly network traffic. |
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| Keywords: | anomaly network traffic detection clustering algorithm fuzzy C-Means clustering algorithm |
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